E-Warmup
AI-powered email warmup to fix deliverability & reputation
What it does
E-Warmup is an AI-powered email warmup tool that builds sender reputation and fixes deliverability on autopilot. Instead of generic filler, it warms up your inbox using your real outreach content, in 30+ languages. With realistic AI read emulation, live bounce rate tracking, custom ESP sending splits, and automated blacklist repair, E-Warmup protects your domain health and helps you hit up to 98% inbox placement before you scale.
Improve email deliverability & stop landing in spam. Warm up mailboxes automatically in 30 seconds across 30+ languages. Scale your cold outreach with an AI-powered 98% inbox placement rate.
We warm up your email and fix your deliverability automatically, so every send reaches the inbox, not the spam folder. From automated inbox warming to real-time analytics and blacklist monitoring, our platform ensures your emails land where they matter most - the inbox, not spam. E-Warmup combines AI-powered email warmup, real inbox interactions, and global infrastructure to strengthen sender reputation and improve inbox placement across major email providers. Connect your mailbox and start automated email warmup in 25 seconds with no technical setup required. 40,000+ AI-powered real inboxes generating authentic engagement signals to boost inbox placement and strengthen your sender…from e-warmup.com
Does the same job
all alternatives →More growth this month
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AstraPixels▲267A pixel-art solar system at its real current positions.
Growth · 29d ago · astrapixels.com

Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com